Chemie und Prozesstechnik
Filtern
Dokumenttyp
- Vortrag (1069) (entfernen)
Sprache
- Englisch (1069) (entfernen)
Referierte Publikation
- nein (1069)
Schlagworte
- Concrete (39)
- LIBS (36)
- Nanoparticles (32)
- NDT (30)
- Fluorescence (28)
- Traceability (25)
- Synchrotron (24)
- Additive manufacturing (23)
- X-ray scattering (23)
- Metrology (22)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (339)
- 6 Materialchemie (339)
- 8 Zerstörungsfreie Prüfung (287)
- 6.1 Oberflächen- und Dünnschichtanalyse (122)
- 1.1 Anorganische Spurenanalytik (99)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (88)
- 8.0 Abteilungsleitung und andere (87)
- 6.3 Strukturanalytik (84)
- 4 Material und Umwelt (70)
- 1.4 Prozessanalytik (61)
Due to the fast growth of industry and the use of metal-containing compounds such as sewage sludge in agricultural fields, soil pollution associated with heavy metals presents a terrifying threat to the environment. Throughout the world, there are already 5 million sites of soil contaminated by heavy metals1. Some heavy metals pollutants can influence food chain safety and food quality, which in turn affects human health. According to the German Federal Soil Protection and Contaminated Site Ordinance (BBodSchV) 13 heavy metals such as arsenic (As), lead (Pb) and cadmium (Cd) are classified as heavily toxic to human health2. Therefore, elemental analysis and precise quantification of the heavy metals in soil are of great importance.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences3. For the first time, the applicability of MICAP-MS for elemental analysis of environmental soils is investigated in this work. For this purpose, 7 reference- and 3 random soil samples containing vanadium (V), cobalt (Co), zink (Zn), copper (Cu), chrome (Cr), mercury (Hg), As, Pb and Cd are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated using ICP-MS. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Moreover, the performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared
Laser-induced plasmas are widely used in many areas of science and technology; examples include spectrochemical analysis, thin film deposition, and material processing. Several topics will be addressed. First, general phenomenology of laser-induced plasmas will be discussed. Then, a chemical model will be presented based on a coupled solution of Navier-Stokes, state, radiative transfer, material transport, and chemical equations. Results of computer simulations for several chemical systems will be shown and compared to experimental observations obtained by optical imaging, spectroscopy, and tomography. The latter diagnostic tools will also be briefly discussed. Finally, a prospective application of laser-induced plasma and plasma modeling will be illustrated on the example of chemical vapor deposition of molybdenum borides and micro processing and coating of titanium dental implants.
IRWG strategy update
(2022)
In view of the increasing digitization of research and the use of data-intensive measurement and analysis methods, research institutions and their staff are faced with the challenge of documenting a constantly growing volume of data in a comprehensible manner, archiving them for the long term, and making them available for discovery and re-use by others in accordance with the FAIR principles. At BAM, we aim to facilitate the integration of research data management (RDM) strategies during the whole research cycle from the creation and standardized description of materials datasets to their publication in open repositories. To this end, we present the BAM Data Store, a central system for internal RDM that fulfills the heterogenous demands of materials science and engineering labs. The BAM Data Store is based on openBIS, an open-source software developed by the ETH Zurich that has originally been created for life science laboratories but that has since been deployed in a variety of research domains. The software offers a browser-based user interface for the digital representation of lab inventory entities (e.g., samples, chemicals, instruments, and protocols) and an electronic lab notebook for the standardized documentation of experiments and analyses.
To investigate whether openBIS is a suitable framework for the BAM Data Store, we carried out a pilot phase during which five research groups with employees from 16 different BAM divisions were introduced to the software. The pilot groups were chosen to represent a diverse array of domain use cases and RDM requirements (e.g., small vs big data volume, heterogenous vs structured data types) as well as varying levels of prior IT knowledge on the users’ side.
Overall, the results of the pilot phase are promising: While the creation of custom data structures and metadata schemas can be time-intensive and requires the involvement of domain experts, the system offers specific benefits in the form of a simplified documentation and automation of research processes, as well as constituting a basis for data-driven analysis. In this way, heterogeneous research workflows in various materials science research domains could be implemented, from the synthesis and characterization of nanomaterials to the monitoring of engineering structures. In addition to the technical deployment and the development of domain-specific metadata standards, the pilot phase also highlighted the need for suitable institutional infrastructures, processes, and role models. An institute-wide rollout of the BAM Data Store is currently being planned.
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. The growing diversity of construction and demolition waste is leading to increasing difficulties in separating the individual materials. Manual sorting involves many risks and dangers for the executing staff and is merely based on obvious, visually detectable differences for separation. An automated, sensor-based sorting of these building materials could complement or replace this practice to improve processing speed, recycling rates, sorting quality, and prevailing health conditions.
A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) and visual (VIS)/ near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-containing building materials (gypsum, aerated concrete, etc.). Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic/technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.
First LIBS measurements show promising results in distinguishing various material types. A meaningful validation shall be achieved with further practical samples. Future works will investigate the combination of LIBS and VIS/NIR spectroscopy in a fully automated measurement setup with conveyor belt speeds of 3 m/s.
Laser metal deposition is a rapidly evolving method for additive manufacturing that combines high performance and simplified production routine. Quality of production depends on an instrumental design and operational parameters, which require constant control during the process. In this work, feasibility of using optical spectroscopy as a control method is studied via modeling and experimentally. A simplified thermal model is developed based on the time-dependent diffusion-conduction heat equation and geometrical light collection into detection optics. Intense light emitted by a laser-heated spot moving across a sample surface is collected and processed to yield the temperature and other temperature-related parameters. In the presence of surface defects, the temperature field is distorted in a specific manner that depends on shape and size of the defect. Optical signals produced by such the distorted temperature fields are simulated and verified experimentally using a 3D metal printer and a sample with artificially carved defects. Three quantities are tested as possible metrics for monitoring the process: temperature, integral intensity, and correlation coefficient. The shapes of the simulated signals qualitatively agree with the experimental signals; this allows for a cautious inference that optical spectroscopy can detect surface defects and, possibly, predict their characters, e.g., inner or protruding.
A new method combining isotope dilution mass spectrometry (IDMS) and standard addition has been developed to determine the mass fractions w of different elements in complex matrices: (a) silicon in aqueous tetramethylammonium hydroxide (TMAH), (b) sulfur in biodiesel fuel, and (c) iron bound to transferrin in human serum. All measurements were carried out using inductively coupled plasma mass spectrometry (ICP–MS). The method requires the gravimetric preparation of several blends (bi)—each consisting of roughly the same masses (mx,i) of the sample solution (x) and my,i of a spike solution (y) plus different masses (mz,i) of a reference solution (z).
Only these masses and the isotope ratios (Rb,i) in the blends and reference and spike solutions have to be measured. The derivation of the underlying equations based on linear regression is presented and compared to a related concept reported by Pagliano and Meija. The uncertainties achievable, e.g., in the case of the Si blank in extremely pure TMAH of urel (w(Si)) = 90% (linear regression method, this work) and urel (w(Si)) = 150% (the method reported by Pagliano and Meija) seem to suggest better applicability of the new method in practical use due to the higher robustness of regression analysis.
The residual stresses and load transfer in multiphase metal alloys and their composites (with both random planar-oriented short fibers and particles) will be shown, as studied by neutron diffraction, by X-ray computed tomography, and by a model based on the reformulation of classic Maxwell’s homogenization method.
Contrary to common understanding and state-of-the-art models, we experimentally observe that randomly oriented phases possess non-hydrostatic residual stress. Moreover, we disclose that the unreinforced matrix alloy stays under hydrostatic compression even under external uniaxial compression.
The recently developed modeling approach allows calculating the residual stress in all phases of the composites. It rationalizes the presence of deviatoric stresses accounting for the interaction of random oriented phases with fibers having preferential orientation. It also allows the explanation of the unconventional in-situ behavior of the unreinforced alloy and the prediction of the micromechanical behavior of other similar alloys.
The overall interest in nanotoxicity, triggered by the increasing use of nanomaterials in the material and life sciences, and the synthesis of an ever increasing number of new functional nanoparticles calls not only for standardized test procedures1,2 and for efficient approaches to screen the potential genotoxicity of these materials, but also for standardized and validated methods for surface analysis.
4,5 The analysis and quantification of surface chemistry is hence in the focus of an increasing number of standardization organizations and interlaboratory comparisons with different analytical methods are being done.5 For the monitoring of nanomaterial synthesis and the fast assessment of the number of functional groups such as carboxyl and amino functionalities, which are very commonly used functionalities in the life sciences, simple and validated methods are needed that can be performed with common laboratory instrumentation. 5,6 Here we provide a brief overview of the ongoing research in division Biophotonics employing quantitative NMR (qNMR), conductometry, and colorimetric and fluorometric optical assays for the determination of the total and the accessible number of carboxyl and amino groups on differently sized polymer and silica nano- and microparticles.5-7
The fabrication of laser-generated surface structures on titanium and titanium alloys has recently gained remarkable interests, being technologically relevant for applications in optics, medicine, fluid transport, tribology, and wetting of surfaces. The morphology of these structures, and so their chemistry, is influenced by the different laser processing parameters such as the laser fluence, wavelength, pulse repetition rate, the effective number of laser pulses per beam spot area, etc. A simple way to characterize laser-generated surface structures is by means of optical microscopy (OM) or white light interference microscopy (WLIM). The latter can address the surface topography, while having a lateral resolution limit of ~(lambda)/2 (lambda = illumination wavelength). To resolve morphologies with spatial periods significantly smaller than (lambda)/2, scanning electron microscopy (SEM) is often used, taking benefit of the reduced de Broglie wavelength associated to the electrons of several keV energy. However, all the above-mentioned techniques lack the necessary depth-resolution to reveal and quantify sub-surface material modifications of these laser-generated structures. Time-of-Flight secondary ion mass spectrometry (ToF-SIMS) represents a promising surface analytical technique for studying laser-induced chemical surface alterations since the method combines a high surface sensitivity with the capability to perform a depth-profiling of the laser-affected surface zone. In this study we combine WLIM and high-resolution SEM with ToF-SIMS to fully characterize the evolution of various types of laser-generated micro- and nanostructures formed on Ti-6Al-4V alloys upon irradiation by near infrared ultrashort laser pulses (1030 nm, 925 fs) at different laser fluence levels, effective number of pulses, and at different pulse repetition rates (1 – 400 kHz). We show how this combined surface analytical approach allows to evaluate alterations in the surface chemistry and topography of the laser-generated surface structures depending on the laser processing parameters
Nanoforms with at least one dimension below 100 nm have an important part to play in more and more areas of our daily life. Therefore, risk assessment of these materials is becoming increasingly important. In this context, the European Chemical Agency (ECHA) considered eleven physico-chemical properties as relevant, of which the following six are essential for the registration: chemical composition, crystallinity, particle size, particle shape, surface chemistry and specific surface area. Four of these priority properties can be obtained with electron microscopy and surface analytics like XPS and ToF-SIMS. The reliability of this data must be ensured, especially for their use for grouping and read across approaches. On the other hand, the “reproducibility” crisis has revealed major shortcomings in the reliability of published data.
In a case study, we show how the quality of the data can be ensured by using existing standards and protocols of each step in the workflow of sample characterization. As exemplary samples, two Al-coated TiO2 samples as nanopowders were selected from the JRC repository, capped either with a hydrophilic or a hydrophobic organic ultrathin shell. SEM results provided the size and shape of the nanoparticles, a first overview about the composition was obtained with EDS. XPS and ToF-SIMS supplied the surface chemistry, especially information about the shell and the coating of the particles. Standards and protocols of all steps of the analytical workflow including preparation and data reduction are discussed regarding reliable and reproducible data. Additionally, uncertainties for the different steps are specified.
Only such a detailed description of all these factors allows a comprehensive physico-chemical characterization of the nanoparticles with understanding of their potential risk assessment.
VAMAS-Enabling international standardisation for increasing the take up of Emerging Materials
(2022)
VAMAS (Versailles Project on Advanced Materials and Standards) supports world trade in products dependent on advanced materials technologies by providing technical basis for harmonized measurements, testing, specification, reference materials and standards. The major tools for fulfilling this task are interlaboratory comparisons (ILC). The organisation structure of VAMAS is presented. It is discussed, how a new technical activity can initiate.
In the face of rising energy demand and the impending climate change the development of a sustainable, fossil-free fuel and chemical production is of global importance. One possible goal is the development of electrochemical conversion processes using catalysts. Porous materials play an important role in such energy applications. The activity and stability of each catalyst is highly dependent on the properties of the coating, i.e., phase composition, crystallinity, accessible surface area, and many other factors. The key to the development of improved catalysts is a better understanding of the relations between their performance, stability and physico-chemical properties. However, the complex morphology of such catalysts constitutes a challenge even for modern analytical techniques. Spectroscopic ellipsometry (SE) is a versatile method for studying material properties by using appropriate models (e.g., film thickness, optical and electronic properties). Ellipsometric models need to be validated in order to produce accurate results. In a first step, the model for the ellipsometric fit studies of a calcination series of mesoporous iridium oxide films (300 – 600 °C) was investigated and validated with respect to their material properties.[4] The information on electronic structure of the catalysts shows a direct correlation with electrochemical activities. The development of an environmental electrochemical cell offers the possibility of investigations under operando conditions. Thus, changes in optical and electronic properties can be induced and monitored during the electrocatalytic oxygen evolution reaction.
A brief introduction is given into our data collection and organization procedure, and why we have settled on the HDF5-based NeXus format for describing experimental data.
The links between NeXus and the SciCat data catalog is also provided, showing how the NeXus metadata is automatically added as searchable metadata in the catalog.
Due to the diffusive nature of heat propagation in solids, the detection and resolution of internal defects with active thermography based non-destructive testing is commonly limited to a defect-depth-to-defect-size ratio greater than or equal to one. In the more recent past, we have already demonstrated that this limitation can be overcome by using a spatially modulated illumination source and photothermal super resolution-based reconstruction. Furthermore, by relying on compressed sensing and computational imaging methods we were able to significantly reduce the experimental complexity to make the method viable for investigating larger regions of interest. In this work we share our progress on improving the defect/inhomogeneity characterization using fully 2D spatially structured illumination patterns instead of scanning with a single laser spot. The experimental approach is based on the repeated blind pseudo-random illumination using modern projector technology and a high-power laser. In the subsequent post-processing, several measurements are then combined by taking advantage of the joint sparsity of the defects within the sample applying 2D-photothermal super resolution reconstruction. Here, enhanced nonlinear convex optimization techniques are utilized for solving the underlying ill-determined inverse problem for typical simple defect geometries. As a result, a higher resolution defect/inhomogeneity map can be obtained at a fraction of the measurement time previously needed.
Additively manufactured (and in particular laser powder bed fused) materials represent a manyfold challenge for the materials scientist and engineer because of their distinctive microstructure. If laser powder bed fusion is used to produce components, the complexity level increases because meso-structures (e.g., overhanging features, surface and internal defects) gain importance. Furthermore, if the main advantage of additive manufacturing, i.e., the freedom of design, is to be fully exploited, and geometrically complex structures, such as lattices, are manufactured, then such structures become meta-materials. This means that the geometry and the materials properties become equally important.
This matryoshka-like (more literary than the dry “multi-scale”) complexity makes the characterization of the residual stress fields by means of diffraction methods so difficult with the current means, that new paradigms are necessary to tackle the challenge.
Indeed, classic open problems acquire an extra layer of difficulty, such that new solutions need to be found and the sometimes-dormant debate needs to be re-opened. Examples include the determination of: a- the unstrained reference: this reference can become location-dependent and needs to be carefully determined; b- the so-called diffraction elastic constants, which becomes immensely challenging since even the single-crystal elastic constants are not known for additively manufactured materials.
On top of this, other problems arise. The determination of the principal axes of stress becomes non-trivial because the hatching strategy sometimes dominates over the sample geometry. Even further, in complex structures, such as lattices, the textbook statement that the strain measurement in six independent directions uniquely identifies the strain tensor becomes simply invalid. The peculiar surface features of additively manufactured materials transform trivial tasks into formidable challenges: the precise alignment of a specimen in a beam or the determination of surface stresses with laboratory X-rays need to be thoroughly re-discussed and lay far from being routine tasks.
In this paper, we will show a few examples of the cases mentioned above. We will demonstrate that sometimes the classic approach works very well, but other times surprising conclusions can be drawn from in-depth studies of the residual stress in additively manufactured materials. In short, we predicate that classic methods cannot be used on additively manufactured materials and structures without a critical evaluation of their validity and application range.
Quality assessment of components produced by metal based additive manufacturing (AM) technologies such as laser powder bed fusion is rising in importance due to the increased use of AM in industrial production. Here, the presence of internal porosity was identified as a limiting factor for the final component quality. The utilization of thermography as an in-situ monitoring technique allows the determination of the part’s thermal history which was found to be connected to the porosity formation [1]. Combining the local thermal information derived from thermography with the porosity information obtained by x-ray micro computed tomography, machine learning algorithms can be utilized to predict the porosity distribution in the part. In this study, a first approach for the prediction of keyhole porosity in a cylindric specimen from AISI 316L stainless steel is presented. It is based on data augmentation using the “SmoteR” algorithm [2] to cure the dataset imbalance and a 1-dimensional convolutional neural network.
[1] C.S. Lough et al., Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared thermal feature porosity probability maps. Journal of Materials Processing Technology, 302, p. 117473 (2022)
https://dx.doi.org/10.1016/j.imatprotec.2021.117473
[2] L. Torgo et al., SMOTE for Regression. Progress in Artificial Intelligence, Chapter 33, p. 378-289 (2013)
https://dx.doi.org/10.1007/978-3-642-40669-0_33
Atmospheric pressure plasmas interact in various physical ways with their surroundings. They release heat and generate charge carriers, which leads to two effects. The first effect is the generation of acoustic waves due to heat release, known as the thermoacoustic effect, and the second effect is the perturbation of the resting fluid provoked by the release of charge carriers, called “ionic wind”. The direct connection between the charge carrier production of the discharge arrangement and the surroundings also allows the detection of acoustic waves by tracking the electrical current of the arrangement.
This contribution introduces a multi-fluid model approach to describe the acoustic interaction of atmospheric plasmas. In addition, we present experimental results on commercially available and in-house fabricated discharge arrangements for either emitting or receiving acoustic waves.
The prerequisites for a successful energy transition and the economic use of hydrogen as a clean green energy carrier and for H2 readiness are a rapid market ramp-up and the establishment of the required value chains. Reliable quality and safety standards for innovative technologies are the prerequisite for ensuring supply security, for environmental compatibility and sustainable climate protection, for building trust in these technologies and thus enable product and process innovations.
With the Competence Centre "H2Safety@BAM", BAM is creating the safety-related prere-quisites for the successful implementation of hydrogen technologies at national as well as European level. BAM uses decades of experience in dealing with hydrogen technologies to develop the necessary quality and safety standards.
The presentation will draw a bow from the typical basic tasks of BAM in the field of competence "Sensors, analytics and certified reference materials", such as maintenance and dissemination of the national gas composition standards for calorific value determination as Designated Institute for Metrology in Chemistry within the framework of the Metre Convention, to the further development of measurement and sensor technology for these tasks. For the certification of reference materials, a mostly slow and time-consuming but solid reference analysis is common. With hydrogen and its special properties, completely new requirements are added. In addition, fast and simple online analysis is required for process control, for example to register quality changes, e.g., during load changes or refuelling processes.
Dust deposition is an important source of phosphorus (P) to many ecosystems. However, there is little evidence of dust-derived P-containing minerals in soils. Here we studied P forms along a well-described climatic gradient on Hawaii, which is also a dust deposition gradient. Soil mineralogy and soil P forms from six sites along the climatic gradient were analyzed with bulk (X-ray diffraction and P K-edge X-ray absorption near edge structure)
and microscale (X-ray fluorescence, P K-edge X-ray absorption near edge structure, and Raman) analysis methods. In the wettest soils, apatite grains ranging from 5 to 30 μm in size were co-located at the micro-scale with quartz, a known continental dust indicator suggesting recent atmospheric deposition. In addition to colocation with quartz, further evidence of dust-derived P included backward trajectory modeling indicating that dust particles could be brought to Hawaii from the major global dust-loading areas in central Asia and northern Africa. Although it is not certain whether the individual observed apatite grains were derived from long-distance transport of dust, or from local dust sources such as volcanic ash or windblown fertilizer, these observations offer direct evidence that P-containing minerals have reached surface layers of highly-weathered grassland soils
through atmospheric deposition.
The fabrication of nanostructures with ever-decreasing sizes has increased the demand of suitable characterization methods which allow to determine their shape and size at the true nanoscale, and similarly important, enable the investigation of their optical properties beyond the diffraction limit. Due to its high spectral and spatial resolution down to the (sub-) nanometer range, electron beam-based techniques, namely cathodoluminescence (CL) has become a powerful characterization tool, particularly to study plasmonic and dielectric nanostructures. However, the interpretation of the resulting spectral CL maps is not always unambiguously straightforward.
In this work, Mie resonances in single Si nanospheres of different sizes have been systematically studied, using experimental CL spectroscopy and an analytical CL model. For smaller spheres (r ~ 75 nm), the eigenmodes can be unequivocally identified, with relative changes in intensity of the electric and magnetic dipole depending on the electron beam position within the sphere. However, in larger spheres (r ~ 105 nm), the modal assignment becomes increasingly difficult due to a larger number of Mie modes in the visible spectral range. Additionally, penetrating electron beams generate two radiating dipoles at the two Si interfaces – due to the electron and its image charge collapsing at those interfaces – which can, depending on the electron beam’s velocity and its path length inside the particle, produce distinct resonances or dips (constructive or destructive interference of those two radiative dipoles). It is demonstrated that superimposed on the eigenmodes of the studied nanospheres, these resonances can distort the recorded spectrum and lead to potentially erroneous assignment of modal characters to the spectral features. An intuitive analogy is developed to unambiguously distinguish those resonance induced by transition radiation from the nanoparticle-specific Mie resonances.
In current Li-ion batteries electrode materials consist typically of inorganic materials, such as LiCoO2, LiNixCoyMn1-zO2, LiFePO4, Li4Ti5O12. These materials struggle with toxicity or limited mineral resources, making them expensive. Therefore, eco-friendly, sustainable, and low-cost alternatives are researched for in recent years. A series of organic compounds were investigated as electrode materials for alkali-ion batteries. Among them organic carbonyl-based materials show reversible storage of lithium- or sodium-ions. Metal terephthalates stand out with their easy synthesis, moderate operational voltage and enhanced dissolution stability compared to other organic compounds. One degradation pathway consists of the dissolution of the electrode material by HF, formed in a side reaction by water and the fluorous electrolyte. Fluorinated metal terephthalates could offer higher dissolution stability against HF and less contamination by water due to their increased hydrophobicity.
The goal of this project is the synthesis and the investigation of the formation mechanism of a series of calcium-based MOFs with increasing fluorine content. For this purpose, we aimed for the construction of calcium-based MOFs with terephthalic acid (H2-pBDC), 2-fluoro-terephthalic acid (H2-2F-pBDC), 2,3,4,5-tetrafluoroterephthalic acid (H2-pBDC-F4), isophthalic acid (H2-mBDC) and 5-fluoro-isophthalic acid (H2-5F-mBDC).
Colours, nano and surface
(2022)
The basic ideas of colours and pigments are presented. The correlation between nanomaterials and colours are explained. Different methods are presented for investigating nanoparticles and their surface. At the end a case study is presented explaining the importance of coating for the properties of nanoparticles.
A brief introduction will be given on modeling chemical reactions in laser induced plasmas using stoichiometric and non-stoichiometric approaches. Several applications will be considered, which can benefit from such modeling. Those include plasma enhanced chemical vapor deposition (PECVD), surface modification and surface coating, and molecular analysis by LIBS. Each application will be illustrated by simulations of relevant chemical systems. For PECVD, chemical systems are BCl3/H2/Ar, BF3/H2/Ar, BCl3/BF3, Mo/BF3/H2; for surface modification/coating it is Ti/air; for molecular LIBS they are CaCO3/Ar, Ca(OH)2/Ar, and CaCl2/Ar. Advantages and shortcomings of equilibrium chemical hydrodynamic models of laser induced plasmas will be discussed.
Alternative to conventional transmission-based radiography and computed tomography, X-ray refraction techniques are being increasingly used to detect damage in light materials. In fact, their range of application has been recently extended even to metals. The big advantage of X-ray refraction techniques is that they are able to detect nanometric defects, whose size would lie below the resolution of even state-of-the-art synchrotron-based X-ray computed tomography (SXCT). The superiority of synchrotron X-ray refraction radiography and tomography (SXRR and SXRCT) has been shown in the case of light materials, in particular composites. X-ray refraction techniques also yield a quantitifaction of the amount of damage (the so-called relative internal specific surface) and can well be compared with damage models. At the same time, it is impossible for SXRR and SXRCT to image single defects. We show that the combination of refraction- and transmission-based imaging techniques yields an impressive amount of additional information about the type and amount of defects in microstructured materials such as additively manufactured metals or metal matrix composites. We also show that the use of data fusion techniques allows the classification of defects in statistically significant representative volume elements.
Turbine blades for gas turbines are exposed to extreme working conditions in a demanding environment. In-service inspection, maintenance and refurbishment of the heavily stressed parts is necessary to ensure both safety and efficiency, e.g. based on immersion ultrasound testing (UT).
In the course of NDE 4.0, the European project MRO 2.0 aims to innovate the maintenance, repair and overhaul of turbine blades by linking these with modern digital methods. For this, the goal of this project is to go beyond conventional automated and manual UT testing techniques.
The aim is to measure the actual geometry and wall thickness of the complex shaped parts by applying an adaptive TFM that takes into account the refraction of the ultrasonic waves at the transition from the coupling material (water) to the inspected part (steel). In this setup the phased array probe is held by a robotic arm that allows the part to be scanned while remaining mainly perpendicular to the inspected surface. In this way, even complex geometries can be inspected and a 3D model of the actual condition of the part can be created.
The laboratory setup is equipped with a Vantage 64 phased array instrument from Verasonics Inc. and an industrial robot from ABB. A 64 element linear array probe operating at 10 MHz is attached to the robot.
The focus is on optimizing resolution, reliability and inspection speed, as the reconstructed model will be fed to the digital twin at a later stage of the project and used for targeted repairs. In addition to enhancing the reconstruction algorithms, required probe geometry and the parameters needed to inspect turbine blades with partially thin walls and anisotropic materials will also be investigated.
This talk will describe the 3-year project and present the results of the first year. The main focus will be on the development of the reconstruction algorithms used and the experimental setup.
Surface modification of titanium by laser ablation is investigated theoretically and experimentally. The modification consists in texturing the surface and redeposition of chemically transformed material from the ablation plasma. The redeposition is driven by the hydrodynamic flow in the plasma. Such surface modification improves the biocompatibility of titanium implants.
This course will provide an introduction to plasma diagnostic techniques. The major focus of the course will be on the discussions of the practical procedures as well as the underlying physical principles for the measurements of plasma fundamental characteristics (e.g., temperatures and electron number density). Particular emphasis will be placed on laser induced plasma–atomic emission spectrometry, but other analytical plasmas will also be used as examples when appropriate. Selected examples on how one can manipulate the operating conditions of the plasma source, based on the results of plasma diagnostic measurements, to improve its performance used for spectrochemical analysis will also be covered. Topics to be covered include thermal equilibrium, line profiles, temperatures, electron densities, excitation processes, temporal and spatial resolution.
Um aus messtechnisch ermittelten Dispersionsabbildungen geführter Ultraschallwellen Rückschlüsse auf die Materialparameter zu ziehen, werden in der aktuellen Forschung verschiedene inverse Methoden diskutiert. Maschinelles Lernen und insbesondere Convolutional-Neural-Networks (CNNs) stellen eine Möglichkeit der automatisierten inversen Modellierung und Evaluierung von Bilddaten dar. In diesem Vortrag wird anhand synthetischer Daten gezeigt, wie das Ausbreitungsverhalten von geführten Ultraschallwellen unter Verwendung von CNNs genutzt werden kann, um die isotropen elastischen Konstanten einer plattenförmigen Struktur zu bestimmen.
There are many different methods to characterize air-coupled ultrasonic transducers for non-destructive testing. Data sheets of various manufacturers contain information about some parameters important for the performance of transducers, but this information is not standardized, so that a comparison between probes of different manufacturers is difficult. Therefore, the German Society for Non-Destructive Testing (DGZfP) is working on a guideline to characterization of air-coupled probes.
One of the topics in this guideline is the application of thermoacoustic transducers for the characterization of receivers and another topic is the application of microphones for the characterization of transmitters. In this presentation we compare various characterization methods with the particular focus on the characterization of thermoacoustic transducers using an optical microphone. Both thermoacoustic transmitters and optical microphones have a very large bandwidth compared to conventional air-coupled transducers, but their spectrum is not entirely linear, which needs to be taken into account if they are applied as reference transducers.
Ultrasonic monitoring, making use of the sensitivity of the coda of repeated transmission meas-urements to changes in stress, temperature, moisture, as well as localized or distributed damage, has gotten at-tention in structural health monitoring (SHM) research recently. Analysis methods such as coda wave inter-ferometry (CWI), including its nonlinear extension, have been shown to be able to measure ultrasonic wave velocity changes with a 1∙10-5 resolution, while indicators such as cross-correlation or cross-coherence have been used to distinguish between reversible and irreversible changes. Several small- and large-scale laboratory experiments have demonstrated that stress changes in structures can be captured or damage detected in a very early stage. The use of this technique for pre-warning before failure are currently under investigation, as well as detailed research on the physical causes and the connection between ultrasonic wave properties and materi-al/structural behavior. Recently, several of large-scale laboratory and real structures have been instrumented with embedded ultrasonic transducers to gather experience and evidence on how to use this technology in re-al-world applications. Preliminary results from installations on a new bridge, an existing bridge, a tunnel, a la-boratory earthquake test as well as a historic stadium in Germany, Poland, and the United States, respectively, are presented. Environmental influences (mainly temperature) and validation by load tests are discussed.
Non-destructive testing methods are available in civil engineering for decades to estimate concrete properties or to detect flaws and features. But recently we have seen the dawn of next-generation tools, methods, and applications. Some of them will be discussed in the web talk: – Better tools: deeper and more detailed insight into concrete constructions – Better methods: Quantitative use in probabilistic structural assessment – Better rules: Towards standardization, qualification, and certification – Better application: Digitalization and Elimination of the boundaries between NDT, SHM, and BIM: NDT-CE 4.0 Not enough? I might show, how cosmic rays might become a game-changer in NDT-CE. This live webinar record was provided by https://eurostruct.org
ML@BAMLINE
(2021)
In this talk I’ll describe the use of artificial neural networks (ANN) for quantifying X-ray fluorescence (XRF) measurements. The main idea of this talk is to give an overview of the process needed to generate a model that can then be applied to a specific problem.
In XRF, a sample is excited with X-rays and the resulting characteristic radiation is detected to determine elements quantitatively and qualitatively. This is traditionally done in several time-consuming steps. I’ll show the possibilities and problems of using a neural network to realise a "one-click" quantification. This includes generating training data using Monte Carlo simulation and augmenting the existing data set with an ANN to generate more data. The search for the optimal hyperparameters, manually and automatically, is also described. For the case presented, we were able to train a network with a mean absolute error of 0.1% by weight for the synthetic data and 0.7% by weight for a set of experimental data obtained with certified reference materials.
The determination of the measurement uncertainty of quantitative and qualitative results is an important quality management tool, for example to describe measuring equipment, procedures, measurement results and the quality of products. The lecture presents the process description for the determination of the measurement uncertainty according to GUM, the determination of uncertainties in qualitative measurement results and the application of the measurement uncertainty for conformity assessment.
ML has been successfully applied to solve many NDT-CE tasks. This is usually demonstrated with performance metrics that evaluate the model as a whole based on a given set of data. However, since in most cases the creation of reference data is extremely expensive, the data used is generally much sparser than in other areas, such as e-commerce. As a result, performance indicators often do not reflect the practical applicability of the ML model. Estimates that quantify transferability from one case to another are necessary to meet this challenge and pave the way for real world applications.
In this contribution we invetigate the uncertainty of ML in new NDT-CE scenarios. For this purpose, we have extended an existing training data set for the classification of corrosion damage by a new case study. Our data set includes half-cell potential mapping and ground-penetrating radar measurements. The measurements were performed on large-area concrete samples with built-in chloride-induced corrosion of reinforcement. The experiment simulated the entire life cycle of chloride induced exposed concrete components in the laboratory. The unique ability to monitor deterioration and initiate targeted corrosion initiation allowed the data to be labelled - which is crucial to ML. To investigate transferability, we extend our data by including new design features of the test specimen and environmental conditions. This allows to express the change of these features in new scenarios as uncertainties using statistical methods. We compare different sampling and statistical distribution-based approaches and show how these methods can be used to close knowledge gaps of ML models in NDT.
Virtual CT with aRTist
(2021)
Simulation becomes more and more important in modern CT imaging. It is increasingly used to optimize techniques for complex applications, to support the preparation of written procedures, and for educational purposes. The radiographic simulator aRTist is a modelling tool which simulates X-ray imaging using a hybrid analytical and Monte Carlo method to efficiently model the radiation transport. In addition to the relevant physical effects such as absorption, scattering and fluorescence, simplified fast models are employed to describe the characteristics of the X-ray source and the detector. aRTist is well equipped to model realistic X-ray imaging setups due to the ability to load exported CAD object descriptions. A simple CT scan module is contained in aRTist which allows the simulation of standard (circular cone beam) scanning trajectories.
This training session starts with a general introduction to aRTist and will highlight its basic usage. Furthermore, the focus is on the configuration of scan trajectories and batch simulations for virtual CT. The aim is to enable the audience to use the aRTist software for their own experiments in virtual CT.
It is fundamental to determine the machine geometry accurately for dimensional X-ray computed tomography (XCT) measurements. When performing high-accuracy scans, compensation of a non-static geometry, e.g. due to rotary axis errors or drift, might become necessary. Here we provide an overview of methods to determine and account for such deviations on a per projection basis. They include characterisation of stage error motions, in situ geometry measurements, numerical simulations, and reconstruction-based optimization relying on image quality metrics and will be discussed in terms of their metrological performance. Since a radiographic calibration is always required to provide an initial absolute geometry, this method will be presented as well.
High entropy alloys (HEAs) are considered as a new class of alloys containing at least 5 elements with concentrations between 5 and 35 atomic percent. There has been a growing interest in HEAs in the material research field in recent years. Due to their adjustable composition, which enables the modifications of mechanical properties (such as hardness, strength and ductility etc) and their stability at high temperatures, HEAs have been the focus of various studies.
Especially the corrosion behavior of HEAs has been a wide research interest. Since the grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect notable information regarding the high temperature oxidation, we consider it as a useful method to investigate how HEAs behave in corrosive environments.
The main idea of grazing geometry is to enhance the fluorescence signal of the surface. This enables highly sensitive surface analyses of thin protective film on surface in sub-micrometer scale. Position-sensitive area detectors provide information regarding the signal emitted from the sample as a function of emission angle and thus allow depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which lays within a specific energy range provides XANES data to determine oxidation states. Moreover, since GEXRF profiles can also be simulated through physical models (Urbach 1999), they enable us to determine the layer thickness of a given sample in a non-destructive way.
In this contribution, we present the preliminary results of a conceptual study regarding layer properties of CrCoNi medium entropy alloy. The successful implementation of such methodological concept will pave the way for the investigation of more complex alloys with multiple layers, which is planned for the later phases of the project.
Mechanochemistry has emerged as one of the most interesting synthetic protocols to produce new materials. The development of mechanochemistry as a synthetic method is supported by excellent research by many groups worldwide in a wide range of applications. The potential of mechanochemistry is also reflected in the inclusion in IUPAC’s 10 chemical innovations that will change our world’.[1] Solvent-free methodologies lead to unique chemical processes during synthesis with the consequent formation of martials with new properties.2 In this contribution, we will discuss our recent results investigating the formation of (polymorphic) cocrystals, coordination polymers, metal oxides and metal nanoparticles.[3-8] We introduced different setups enabling in situ investigation of mechanochemical reactions using synchrotron XRD combined with Raman spectroscopy and thermography.
Mechanochemistry is increasingly used for synthesizing soft matter materials including metal organic compounds and cocrystals.1 The ever-increasing interest in this method is contrasted by a limited mechanistic understanding of the mechanochemical reactivity and selectivity. Time-resolved in situ investigations of milling reactions provide direct insights in the underlying mechanisms.2-4 We recently introduced different setups enabling in situ investigation of mechanochemical reactions using synchrotron XRD combined with Raman spectroscopy and thermography. The presented setup allows the detection of crystalline, amorphous, eutectic, and liquid intermediates. Furthermore, the chemical composition of the reaction mixture was found to be directly correlated with changes in the temperature profile of the reaction. The resulting deeper kinetic and thermodynamic understanding of milling processes is the key for future optimization of mechanochemical syntheses. In this contribution, we will discuss our recent results investigating the formation of (polymorphic) cocrystals and coordination polymers.2,3,5 Our results indicate that in situ investigation of milling reactions offer a new approach to tune and optimize mechanochemical syntheses.